Quantum Particle Swarm Optimization for Multi-objective Combined Economic Emission Dispatch Problem

QPSO is applied to solve multi-objective CEED problem using cubic cost function
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Updated 31 Oct 2017

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In this code, quantum particle swarm optimization (QPSO) is utilized to solve multiobjective combined economic emission dispatch (CEED) problem formulated using cubic criterion function considering a uni wise max/max price penalty factor. QPSO is implemented on a 6-unit power generation system and compared with Lagrangian relaxation, particle swarm optimization (PSO) and simulated annealing (SA). The obtained results verified the effectiveness and demonstrate the robustness of QPSO method. This research suggests that QPSO can be used as an effective and robust tool in other power dispatch problems.

Cite As

Fahad Mahdi (2024). Quantum Particle Swarm Optimization for Multi-objective Combined Economic Emission Dispatch Problem (https://www.mathworks.com/matlabcentral/fileexchange/64896-quantum-particle-swarm-optimization-for-multi-objective-combined-economic-emission-dispatch-problem), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
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Version Published Release Notes
1.0.0.0